(* Content-type: application/vnd.wolfram.mathematica *)

(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)

(* CreatedBy='Mathematica 13.2' *)

(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[       158,          7]
NotebookDataLength[     71327,       1254]
NotebookOptionsPosition[     70532,       1232]
NotebookOutlinePosition[     71044,       1251]
CellTagsIndexPosition[     71001,       1248]
WindowFrame->Normal*)

(* Beginning of Notebook Content *)
Notebook[{

Cell[CellGroupData[{
Cell[BoxData[{
 StyleBox[
  RowBox[{"Clear", "[", "\"\<`*\>\"", "]"}],
  FontColor->RGBColor[0., 0., 0.]], "\[IndentingNewLine]", 
 StyleBox[
  RowBox[{
   RowBox[{"data", "=", 
    RowBox[{
    "Import", "[", "\"\<Mathematica/Experiment10/SDS00012.CSV\>\"", "]"}]}], 
   ";"}],
  FontColor->RGBColor[0., 0., 0.]], "\[IndentingNewLine]", 
 RowBox[{
  StyleBox[
   RowBox[{
    RowBox[{"data", "=", 
     RowBox[{"Drop", "[", 
      RowBox[{"data", ",", " ", 
       RowBox[{"{", "}"}], ",", " ", 
       RowBox[{"{", "3", "}"}]}], "]"}]}], ";"}],
   FontColor->RGBColor[0., 0., 0.]], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 StyleBox[
  RowBox[{
   RowBox[{"peaks", "=", 
    RowBox[{"FindPeaks", "[", 
     RowBox[{
      RowBox[{"data", "[", 
       RowBox[{"[", 
        RowBox[{"All", ",", "2"}], "]"}], "]"}], ",", "300"}], "]"}]}], ";"}],
  FontColor->RGBColor[0., 0., 0.]], "\[IndentingNewLine]", 
 RowBox[{
  StyleBox[
   RowBox[{
    RowBox[{"peaks", "=", 
     RowBox[{"Map", "[", 
      RowBox[{
       RowBox[{
        RowBox[{"{", 
         RowBox[{
          RowBox[{"data", "[", 
           RowBox[{"[", 
            RowBox[{
             RowBox[{"IntegerPart", "[", 
              RowBox[{"#", "[", 
               RowBox[{"[", "1", "]"}], "]"}], "]"}], ",", "1"}], "]"}], 
           "]"}], ",", " ", 
          RowBox[{"#", "[", 
           RowBox[{"[", "2", "]"}], "]"}]}], "}"}], "&"}], ",", "peaks"}], 
      "]"}]}], ";"}],
   FontColor->RGBColor[0., 0., 0.]], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 StyleBox[
  RowBox[{
   RowBox[{"ListLinePlot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{"data", ",", "peaks"}], "}"}], ",", 
     RowBox[{"PlotRange", "->", "All"}], ",", 
     RowBox[{"Joined", "->", 
      RowBox[{"{", 
       RowBox[{"True", ",", " ", "False"}], "}"}]}], ",", " ", 
     RowBox[{"PlotStyle", "->", 
      RowBox[{"{", 
       RowBox[{"PointSize", "[", "0.02", "]"}], "}"}]}]}], "]"}], 
   "\[IndentingNewLine]"}],
  FontColor->RGBColor[0., 0., 0.]], "\[IndentingNewLine]", 
 RowBox[{
  StyleBox["differences",
   FontColor->RGBColor[0., 0., 0.]], 
  StyleBox["=",
   FontColor->RGBColor[0., 0., 0.]], 
  RowBox[{
   RowBox[{"peaks", "[", 
    RowBox[{"[", 
     RowBox[{
      RowBox[{"2", ";;"}], ",", "1"}], "]"}], "]"}], "-", 
   RowBox[{"peaks", "[", 
    RowBox[{"[", 
     RowBox[{
      RowBox[{";;", 
       RowBox[{"-", "2"}]}], ",", "1"}], "]"}], 
    "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"Mean", "[", 
   StyleBox["differences",
    FontColor->RGBColor[0., 0., 0.]], "]"}], 
  StyleBox["\[IndentingNewLine]",
   FontColor->RGBColor[0., 0., 0.]], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]"}], "Input",
 CellChangeTimes->{{3.8942414628040185`*^9, 3.8942414979347625`*^9}, {
   3.8942415625908065`*^9, 3.8942416109754353`*^9}, {3.8942417865277433`*^9, 
   3.8942418079264107`*^9}, {3.894241920680725*^9, 3.8942419644367423`*^9}, {
   3.894242032465645*^9, 3.894242077803069*^9}, {3.8942421102965713`*^9, 
   3.894242157005776*^9}, {3.8942422167908993`*^9, 3.894242282326644*^9}, {
   3.894242675996481*^9, 3.894242687023653*^9}, {3.894242730978697*^9, 
   3.894242756206483*^9}, {3.894242850157013*^9, 3.8942429167187996`*^9}, {
   3.8942430884370575`*^9, 3.894243162477389*^9}, {3.894243221886302*^9, 
   3.8942433777388687`*^9}, {3.894243613391514*^9, 3.894243615407741*^9}, {
   3.8942436663454943`*^9, 3.89424370519419*^9}, {3.894243757810102*^9, 
   3.8942438370484943`*^9}, {3.894244128109674*^9, 3.894244137010935*^9}, {
   3.8942442579665823`*^9, 3.894244284332572*^9}, {3.894244328488446*^9, 
   3.8942443396925397`*^9}, {3.8942443822873282`*^9, 
   3.8942443944413195`*^9}, {3.8942634538426914`*^9, 
   3.8942634564747114`*^9}, {3.8942659365513215`*^9, 3.894265976324995*^9}, {
   3.8942669654367123`*^9, 3.8942670442327003`*^9}, {3.894267077063466*^9, 
   3.8942671397230206`*^9}, {3.8942676015947247`*^9, 3.89426761785935*^9}, {
   3.8942678244339213`*^9, 3.8942678402717333`*^9}, {3.8942678719352293`*^9, 
   3.894267896277583*^9}, {3.894267975088416*^9, 3.894267975647908*^9}, {
   3.8942680656537476`*^9, 3.8942680739311705`*^9}, {3.8942703088409357`*^9, 
   3.8942703474117875`*^9}, {3.894270486439205*^9, 3.8942704936481667`*^9}, {
   3.894270561808175*^9, 3.8942706867921867`*^9}, {3.894270723439576*^9, 
   3.8942707626961803`*^9}, {3.8942708833495855`*^9, 
   3.8942710375638113`*^9}, {3.8942711173190303`*^9, 
   3.8942711499695454`*^9}, {3.894271262581379*^9, 3.894271269470688*^9}, 
   3.8942713683157635`*^9, 3.894336082503236*^9, {3.894336213643091*^9, 
   3.8943362710848813`*^9}, {3.894336325907855*^9, 3.894336333946179*^9}, {
   3.8943365499089518`*^9, 3.8943366400246305`*^9}, {3.894336676927169*^9, 
   3.8943367507904387`*^9}, {3.894336829404157*^9, 3.8943368649890375`*^9}, {
   3.894336901419141*^9, 3.8943369236773596`*^9}, {3.8943369653287315`*^9, 
   3.8943369732793293`*^9}, {3.8943371037388716`*^9, 
   3.8943371058534803`*^9}, {3.8943371532770844`*^9, 
   3.8943372615987215`*^9}, {3.8943372932809753`*^9, 3.894337314394708*^9}, {
   3.8943374827727566`*^9, 3.8943374898979917`*^9}, {3.8943376886774983`*^9, 
   3.894337720898179*^9}, {3.8943378386115913`*^9, 3.8943379411313887`*^9}, {
   3.8943379764820356`*^9, 3.894338008307087*^9}, {3.894338350463855*^9, 
   3.8943383876874237`*^9}, {3.8943384217590804`*^9, 
   3.8943384749412003`*^9}, {3.894338545123633*^9, 3.8943385582708235`*^9}, {
   3.8943386624996357`*^9, 3.894338709928961*^9}, {3.894338785302038*^9, 
   3.894338791185976*^9}, {3.8943388280757427`*^9, 3.8943388300564537`*^9}, {
   3.8943388648412404`*^9, 3.894338893726721*^9}, {3.894339139821184*^9, 
   3.894339293592822*^9}, {3.894339328371769*^9, 3.8943393465742416`*^9}, {
   3.894339418030761*^9, 3.8943394738299465`*^9}, {3.894339504947154*^9, 
   3.8943395820893517`*^9}, {3.8943396275200615`*^9, 3.894339707823224*^9}, 
   3.8943398208412333`*^9, {3.894339859151719*^9, 3.8943399187538147`*^9}, {
   3.894340027662796*^9, 3.894340064316782*^9}, {3.8943401719428396`*^9, 
   3.894340174789977*^9}, {3.8943402063111763`*^9, 3.894340206944249*^9}, {
   3.8943402605919642`*^9, 3.894340261273088*^9}, {3.894340304796381*^9, 
   3.8943403666300335`*^9}, {3.8943404477504845`*^9, 
   3.8943404598330526`*^9}, {3.894340503810398*^9, 3.8943405073960457`*^9}, {
   3.8943405390314107`*^9, 3.894340582090391*^9}, {3.894340671075637*^9, 
   3.8943406738662715`*^9}, {3.8943408053048706`*^9, 
   3.8943408141104813`*^9}, {3.8943408708849964`*^9, 3.894340941457056*^9}, {
   3.8943410277818947`*^9, 3.894341044722139*^9}, {3.894341185508135*^9, 
   3.8943411913685613`*^9}, {3.8943412234441442`*^9, 
   3.8943412909752274`*^9}, {3.8943413687092466`*^9, 3.894341398706023*^9}, {
   3.8943415683487687`*^9, 3.8943417005023623`*^9}, 3.8943417768086643`*^9, 
   3.8943418205147653`*^9, {3.8943465318963833`*^9, 3.894346533101303*^9}, {
   3.894346813103454*^9, 3.894346858230201*^9}, {3.8943469372570753`*^9, 
   3.894347043380541*^9}, {3.894347087361525*^9, 3.894347099252758*^9}, {
   3.894350050989133*^9, 3.8943501151088643`*^9}, {3.894350307277774*^9, 
   3.894350338579441*^9}, {3.894350369735897*^9, 3.894350417951858*^9}, {
   3.894350448657713*^9, 3.894350462990904*^9}, {3.8943505050482016`*^9, 
   3.8943505356162877`*^9}, {3.894350573955243*^9, 3.8943505786997986`*^9}, {
   3.894350610563012*^9, 3.894350622362589*^9}, {3.894350655580121*^9, 
   3.8943507301029725`*^9}, {3.894350768764393*^9, 3.894351120468065*^9}, {
   3.8943513185171337`*^9, 3.8943513297255154`*^9}, {3.894351361653292*^9, 
   3.8943513679492564`*^9}, {3.894351403959343*^9, 3.8943514119474163`*^9}, {
   3.8943515473145714`*^9, 3.8943516225837293`*^9}, {3.8943516600357857`*^9, 
   3.8943517070687513`*^9}, {3.8943517564006195`*^9, 
   3.8943517606774817`*^9}, {3.8943517999472156`*^9, 3.894351863623866*^9}, {
   3.8943519589052753`*^9, 3.8943519835689116`*^9}, {3.894352080277111*^9, 
   3.8943521162801137`*^9}, {3.8943522553418617`*^9, 
   3.8943524085462112`*^9}, {3.8943524434441767`*^9, 
   3.8943524509144564`*^9}, {3.894352522432726*^9, 3.89435258886953*^9}, {
   3.894352626581894*^9, 3.8943529025289125`*^9}, {3.8943529444738264`*^9, 
   3.8943530668618917`*^9}, {3.894353170451353*^9, 3.8943531785304546`*^9}, {
   3.894353220593178*^9, 3.894353250807349*^9}, {3.894353347831519*^9, 
   3.8943533608162317`*^9}, {3.8943534114742007`*^9, 3.894353419722039*^9}, {
   3.894353524996874*^9, 3.894353539415823*^9}, {3.894353580916627*^9, 
   3.89435358632693*^9}, {3.8943537374224467`*^9, 3.8943537466787095`*^9}, 
   3.894353799099848*^9, {3.8943540946295123`*^9, 3.8943541152115297`*^9}, {
   3.894354255834798*^9, 3.8943542652044516`*^9}, 3.8943543226974516`*^9, {
   3.8943548477770953`*^9, 3.8943548496840367`*^9}, {3.8943558341844287`*^9, 
   3.8943558388848267`*^9}, {3.8943559373265877`*^9, 3.894355961493272*^9}, {
   3.894356575299865*^9, 3.89435657825449*^9}, 3.894357563646124*^9, 
   3.8943576208633327`*^9, {3.8943576925199127`*^9, 3.894357705077465*^9}, {
   3.894357789333269*^9, 3.894357825328329*^9}, 3.894358309625084*^9, {
   3.8943583928412285`*^9, 3.894358403606992*^9}, {3.89435881396731*^9, 
   3.894358844719449*^9}, {3.8944460827835965`*^9, 3.894446186315584*^9}, {
   3.894446230507468*^9, 3.8944463918359447`*^9}, {3.89444652158853*^9, 
   3.8944465495882387`*^9}, 3.8944466525051775`*^9, {3.8944473012990513`*^9, 
   3.8944473019757376`*^9}, {3.894447550690689*^9, 3.8944476106167517`*^9}, {
   3.8944480128000784`*^9, 3.894448089001607*^9}, {3.8944481332986264`*^9, 
   3.894448498891053*^9}, {3.8944486258802495`*^9, 3.8944486353866496`*^9}, {
   3.8944494599068394`*^9, 3.8944494921790495`*^9}},
 CellLabel->"In[1]:=",ExpressionUUID->"11b69abf-4f02-4246-9995-b6145953e5a7"],

Cell[BoxData[
 GraphicsBox[{{}, {{{}, {}, 
     {RGBColor[0.368417, 0.506779, 0.709798], PointSize[0.02], 
      AbsoluteThickness[1.6], LineBox[CompressedData["
1:eJxcnXdcju/7xktGkpKKZCQjSSSRRD2lpCENyUgiyUhGMuKDJCOZiSQjGclI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       "]]}}, {{}, 
     {RGBColor[0.880722, 0.611041, 0.142051], PointSize[0.02], 
      AbsoluteThickness[1.6], 
      PointBox[{{-0.00082, 5.28}, {-0.0001472, 4.08}, {0.0005168, 3.44}, {
       0.0012052, 2.96}}]}}}, {{}, {}}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->{True, True},
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  DisplayFunction->Identity,
  Frame->{{False, False}, {False, False}},
  FrameLabel->{{None, None}, {None, None}},
  FrameTicks->{{Automatic, Automatic}, {Automatic, Automatic}},
  GridLines->{None, None},
  GridLinesStyle->Directive[
    GrayLevel[0.5, 0.4]],
  Method->{
   "AxisPadding" -> Scaled[0.02], "DefaultBoundaryStyle" -> Automatic, 
    "DefaultGraphicsInteraction" -> {
     "Version" -> 1.2, "TrackMousePosition" -> {True, False}, 
      "Effects" -> {
       "Highlight" -> {"ratio" -> 2}, "HighlightPoint" -> {"ratio" -> 2}, 
        "Droplines" -> {
         "freeformCursorMode" -> True, 
          "placement" -> {"x" -> "All", "y" -> "None"}}}}, "DefaultMeshStyle" -> 
    AbsolutePointSize[6], "DefaultPlotStyle" -> {
      Directive[
       RGBColor[0.368417, 0.506779, 0.709798], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.880722, 0.611041, 0.142051], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.560181, 0.691569, 0.194885], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.922526, 0.385626, 0.209179], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.528488, 0.470624, 0.701351], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.772079, 0.431554, 0.102387], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.363898, 0.618501, 0.782349], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[1, 0.75, 0], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.647624, 0.37816, 0.614037], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.571589, 0.586483, 0.], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.915, 0.3325, 0.2125], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.40082222609352647`, 0.5220066643438841, 0.85], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.9728288904374106, 0.621644452187053, 0.07336199581899142], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.736782672705901, 0.358, 0.5030266573755369], 
       AbsoluteThickness[1.6]], 
      Directive[
       RGBColor[0.28026441037696703`, 0.715, 0.4292089322474965], 
       AbsoluteThickness[1.6]]}, "DomainPadding" -> Scaled[0.02], 
    "RangePadding" -> Scaled[0.05], "OptimizePlotMarkers" -> True, 
    "OptimizePlotMarkers" -> True, 
    "CoordinatesToolOptions" -> {"DisplayFunction" -> ({
        Identity[
         Part[#, 1]], 
        Identity[
         Part[#, 2]]}& ), "CopiedValueFunction" -> ({
        Identity[
         Part[#, 1]], 
        Identity[
         Part[#, 2]]}& )}},
  PlotRange->{{-0.0014, 0.0013996}, {-2.08, 5.28}},
  PlotRangeClipping->True,
  PlotRangePadding->{{
     Scaled[0.02], 
     Scaled[0.02]}, {
     Scaled[0.05], 
     Scaled[0.05]}},
  Ticks->{Automatic, Automatic}]], "Output",
 CellChangeTimes->{
  3.894353750044381*^9, {3.8943538159054*^9, 3.894353822841852*^9}, {
   3.8943538582364845`*^9, 3.8943538619828544`*^9}, 3.8943540965295315`*^9, {
   3.894354193269645*^9, 3.8943542127413316`*^9}, {3.8943542572278395`*^9, 
   3.894354266748275*^9}, 3.894354324465066*^9, {3.8943548525221767`*^9, 
   3.8943548577967005`*^9}, {3.894355940454156*^9, 3.894355963196041*^9}, {
   3.894357565587105*^9, 3.8943575910851035`*^9}, {3.894357707897785*^9, 
   3.8943577192024007`*^9}, {3.894357792331007*^9, 3.8943578257359176`*^9}, 
   3.8943584068042693`*^9, 3.894358514738923*^9, 3.894358837076996*^9, {
   3.8944461107105026`*^9, 3.894446187914879*^9}, {3.8944462353977633`*^9, 
   3.894446264382468*^9}, {3.894446299836986*^9, 3.8944463400866065`*^9}, 
   3.894446372023919*^9, {3.894446534755819*^9, 3.8944465500319943`*^9}, 
   3.8944466566805205`*^9, {3.8944475541933594`*^9, 3.8944475688350782`*^9}, 
   3.8944476304442625`*^9, {3.8944480787068124`*^9, 3.8944480896448193`*^9}, {
   3.8944481343149395`*^9, 3.894448324494112*^9}, {3.894448368384903*^9, 
   3.894448434606165*^9}, 3.8944485010904675`*^9, 3.8944486363984604`*^9, 
   3.894449483673197*^9, 3.894449840062786*^9},
 CellLabel->"Out[6]=",ExpressionUUID->"6c02372c-a074-43d2-acaf-88b224e55ef6"],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"0.0006728`", ",", "0.000664`", ",", "0.0006884`"}], 
  "}"}]], "Output",
 CellChangeTimes->{
  3.894353750044381*^9, {3.8943538159054*^9, 3.894353822841852*^9}, {
   3.8943538582364845`*^9, 3.8943538619828544`*^9}, 3.8943540965295315`*^9, {
   3.894354193269645*^9, 3.8943542127413316`*^9}, {3.8943542572278395`*^9, 
   3.894354266748275*^9}, 3.894354324465066*^9, {3.8943548525221767`*^9, 
   3.8943548577967005`*^9}, {3.894355940454156*^9, 3.894355963196041*^9}, {
   3.894357565587105*^9, 3.8943575910851035`*^9}, {3.894357707897785*^9, 
   3.8943577192024007`*^9}, {3.894357792331007*^9, 3.8943578257359176`*^9}, 
   3.8943584068042693`*^9, 3.894358514738923*^9, 3.894358837076996*^9, {
   3.8944461107105026`*^9, 3.894446187914879*^9}, {3.8944462353977633`*^9, 
   3.894446264382468*^9}, {3.894446299836986*^9, 3.8944463400866065`*^9}, 
   3.894446372023919*^9, {3.894446534755819*^9, 3.8944465500319943`*^9}, 
   3.8944466566805205`*^9, {3.8944475541933594`*^9, 3.8944475688350782`*^9}, 
   3.8944476304442625`*^9, {3.8944480787068124`*^9, 3.8944480896448193`*^9}, {
   3.8944481343149395`*^9, 3.894448324494112*^9}, {3.894448368384903*^9, 
   3.894448434606165*^9}, 3.8944485010904675`*^9, 3.8944486363984604`*^9, 
   3.894449483673197*^9, 3.894449840078412*^9},
 CellLabel->"Out[7]=",ExpressionUUID->"447d4f6e-1d02-4946-a3f4-58d6cdcc3535"],

Cell[BoxData["0.0006750666666666666`"], "Output",
 CellChangeTimes->{
  3.894353750044381*^9, {3.8943538159054*^9, 3.894353822841852*^9}, {
   3.8943538582364845`*^9, 3.8943538619828544`*^9}, 3.8943540965295315`*^9, {
   3.894354193269645*^9, 3.8943542127413316`*^9}, {3.8943542572278395`*^9, 
   3.894354266748275*^9}, 3.894354324465066*^9, {3.8943548525221767`*^9, 
   3.8943548577967005`*^9}, {3.894355940454156*^9, 3.894355963196041*^9}, {
   3.894357565587105*^9, 3.8943575910851035`*^9}, {3.894357707897785*^9, 
   3.8943577192024007`*^9}, {3.894357792331007*^9, 3.8943578257359176`*^9}, 
   3.8943584068042693`*^9, 3.894358514738923*^9, 3.894358837076996*^9, {
   3.8944461107105026`*^9, 3.894446187914879*^9}, {3.8944462353977633`*^9, 
   3.894446264382468*^9}, {3.894446299836986*^9, 3.8944463400866065`*^9}, 
   3.894446372023919*^9, {3.894446534755819*^9, 3.8944465500319943`*^9}, 
   3.8944466566805205`*^9, {3.8944475541933594`*^9, 3.8944475688350782`*^9}, 
   3.8944476304442625`*^9, {3.8944480787068124`*^9, 3.8944480896448193`*^9}, {
   3.8944481343149395`*^9, 3.894448324494112*^9}, {3.894448368384903*^9, 
   3.894448434606165*^9}, 3.8944485010904675`*^9, 3.8944486363984604`*^9, 
   3.894449483673197*^9, 3.894449840094036*^9},
 CellLabel->"Out[8]=",ExpressionUUID->"b7272776-d36c-42e6-b9fa-e7d700ad8841"]
}, Open  ]]
},
WindowSize->{1024.5, 513.75},
WindowMargins->{{-6, Automatic}, {Automatic, -6}},
TaggingRules-><|"SlideshowSettings" -> <|"Toolbar" -> True|>|>,
Magnification:>1.1 Inherited,
FrontEndVersion->"13.2 for Microsoft Windows (64-bit) (2023\:5e741\:670830\
\:65e5)",
StyleDefinitions->"Default.nb",
ExpressionUUID->"f82e98a0-fbd2-45ad-8789-d8186736a92b"
]
(* End of Notebook Content *)

(* Internal cache information *)
(*CellTagsOutline
CellTagsIndex->{}
*)
(*CellTagsIndex
CellTagsIndex->{}
*)
(*NotebookFileOutline
Notebook[{
Cell[CellGroupData[{
Cell[580, 22, 9759, 185, 304, "Input",ExpressionUUID->"11b69abf-4f02-4246-9995-b6145953e5a7"],
Cell[10342, 209, 57457, 977, 263, "Output",ExpressionUUID->"6c02372c-a074-43d2-acaf-88b224e55ef6"],
Cell[67802, 1188, 1387, 21, 35, "Output",ExpressionUUID->"447d4f6e-1d02-4946-a3f4-58d6cdcc3535"],
Cell[69192, 1211, 1324, 18, 35, "Output",ExpressionUUID->"b7272776-d36c-42e6-b9fa-e7d700ad8841"]
}, Open  ]]
}
]
*)

